/topic-analysis

name: topic-analysis
description: Use when analyzing content topics on Xiaohongshu, identifying trending themes, researching audience interests, evaluating topic performance, or planning content around high-engagement topics

Topic Analysis (话题分析)

Overview

Topic analysis is the systematic examination of content themes, subject matters, and conversation trends on Xiaohongshu to understand what resonates with audiences, identify emerging opportunities, and make data-driven content planning decisions.

When to Use

• Identifying trending topics and themes
• Analyzing which topics drive engagement
• Researching audience interests and preferences
• Evaluating content topic performance over time
• Planning content around proven themes
• Discovering content gaps and opportunities
• Measuring brand topic alignment

Core Pattern

**Before**: Random content, guessing topics, inconsistent themes **After**: Data-driven topics, proven themes, strategic content

**5 Topic Dimensions**: 1. Performance Topics (high engagement, proven winners) 2. Trending Topics (rising popularity, time-sensitive) 3. Evergreen Topics (consistent performance, reliable) 4. Niche Topics (underserved, opportunity-rich) 5. Brand Topics (core to brand identity, strategic)

Quick Reference

| Topic Type | Engagement | Competition | Longevity | Best For | |------------|------------|-------------|-----------|----------| | Performance | High | Varies | Varies | Capitalize on success | | Trending | Spike | Low-Medium | Short | Timely content | | Evergreen | Consistent | High | Long | Sustainable growth | | Niche | Medium | Low | Medium | Differentiation | | Brand | Building | Varies | Long | Brand positioning |

Implementation

Step 1: Collect Topic Data

**Data Sources**:

• Your content performance by topic
• Competitor topic analysis
• Platform trending topics
• Audience questions and requests
• Search trends and suggestions
• Seasonal topic patterns

**Build Topic Database**: Track: Topic name, post count, avg engagement, trend direction, last covered, priority

Step 2: Analyze Topic Performance

**Topic Metrics**:

• Engagement rate per topic
• Reach and impressions
• Follower growth by topic
• Save and share rates
• Comment sentiment by topic
• Conversion rate by topic

**Performance Categories**:

• Star topics (top 10% performers)
• Strong topics (top 25%)
• Average topics (middle 50%)
• Weak topics (bottom 25%)
• Avoid topics (consistently underperform)

Step 3: Identify Topic Trends

**Trend Analysis**:

• Rising topics (momentum increasing)
• Stable topics (consistent performance)
• Declining topics (losing interest)
• Seasonal patterns (predictable cycles)
• Viral spikes (sudden popularity)

**Trend Detection**:

• Week-over-week change
• Month-over-month change
• Seasonal comparison (same period last year)
• Platform trend alignment

Step 4: Map Topics to Content Strategy

**Topic Allocation**:

• 40% Star topics (proven winners)
• 30% Trending topics (timely relevance)
• 20% Evergreen topics (consistency)
• 10% Experimental topics (innovation)

**Content Calendar Integration**:

• Schedule star topics during peak times
• Plan trending topics while hot
• Evergreen topics for consistency
• Test topics in low-risk time slots

Step 5: Monitor Topic Saturation

**Saturation Indicators**:

• Declining engagement on topic
• Increased competition
• Audience fatigue (comments like "again?")
• Diminishing returns over time

**Refresh Strategy**:

• New angle on same topic
• Different format (video vs post)
• Update with new information
• Pause over-saturated topics

Real-World Impact

**Topic Analysis Results**:

• Content engagement +40% from topic optimization
• Follower growth +60% from trending topics
• Saved 50% time on content planning
• Identified 15 underserved niche topics

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Related Skills

**REQUIRED**: Use data-analytics (quantitative analysis) **REQUIRED**: Use content-performance-analysis (topic-specific metrics)

**Recommended**:

• trend-analysis, audience-research, content-strategy